Please find my CV in
Last update: November 1, 2018
|PhD (ongoing)||Computer and Communication Sciences (EDIC)||École Polytechnique Fédérale de Lausanne, Switzerland||September 2013 - present|
|BSc||Electrical and Electronics Engineering||Middle East Technical University, Turkey||September 2009 - June 2013|
|BSc||Physics||Middle East Technical University, Turkey||September 2009 - June 2013|
Fields of expertise
Convex optimization: theory and applications
V. Cevher; C. B. Vu; A. Yurtsever : Inertial Three-Operator Splitting Method and Applications ; SIAM Conference on Optimization - OP17, Vancouver, British Columbia, Canada, May 22-25, 2017.
A. Yurtsever; S. Sra; V. Cevher : Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator. 2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.
A. Yurtsever; O. Fercoq; V. Cevher : A Conditional Gradient-Based Augmented Lagrangian Framework. 2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.
A. Yurtsever; O. Fercoq; F. Locatello; V. Cevher : A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming. 2018-07-11. the 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 10-15, 2018.
K. Y. Levy; A. Yurtsever; V. Cevher : Online Adaptive Methods, Universality and Acceleration. 2018-07-04. 32nd Conference on Neural Information Processing Systems conference (NIPS 2018), Montreal, Canada, December 3-8, 2018.
Y.-P. Hsieh; Y.-C. Kao; R. Karimi Mahabadi; Y. Alp; A. Kyrillidis et al. : A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization; IEEE Transactions on Signal Processing. 2018. DOI : 10.1109/TSP.2018.2870353.
V. Cevher; C. B. Vu; A. Yurtsever : Stochastic Forward-Douglas-Rachford Splitting for Monotone Inclusions; Stochastic Forward Douglas-Rachford Splitting Method for Monotone Inclusions; Springer International Publishing, 2018.
J. A. Tropp; A. Yurtsever; M. Udell; V. Cevher : Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. 2017-12-04. 31st Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, California, USA, December 4-9, 2017.
J. A. Tropp; A. Yurtsever; M. Udell; V. Cevher : Practical Sketching Algorithms For Low-Rank Matrix Approximation; Siam Journal On Matrix Analysis And Applications. 2017. DOI : 10.1137/17M1111590.
A. Yurtsever; M. Udell; J. A. Tropp; V. Cevher : Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage. 2017. 20th International Conference on Artificial Intelligence and Statistics (AISTATS2017), Fort Lauderdale, Florida, USA, April 20-22, 2017.
A. Yurtsever; C. B. Vu; V. Cevher : Stochastic Three-Composite Convex Minimization. 2016. 30th Conference on Neural Information Processing Systems (NIPS2016), Barcelona, Spain, December 5-10, 2016.
J. A. Tropp; A. Yurtsever; M. Udell; V. Cevher : Randomized Single-View Algorithms for Low-Rank Matrix Approximation. 2016.
G. Odor; Y.-H. Li; A. Yurtsever; Y.-P. Hsieh; Q. Tran Dinh et al. : Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval. 2016. 41st IEEE International Conference on Acoustics, Speech and Signal Processing. p. 6230-6234.
A. Yurtsever; Y.-P. Hsieh; V. Cevher : Scalable Convex Methods for Phase Retrieval. 2015. 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Cancun, Mexico, December 13-16, 2015.
A. Yurtsever; Q. Tran Dinh; V. Cevher : A Universal Primal-Dual Convex Optimization Framework. 2015. 29th Annual Conference on Neural Information Processing Systems (NIPS2015), Montreal, Canada, December 7-12, 2015.